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Trends in Applied Sciences Research
Year: 2015  |  Volume: 10  |  Issue: 1  |  Page No.: 68 - 76

A Novel Approach for Arbitrary-Shape ROI Compression of Medical Images Using Principal Component Analysis (PCA)

Lim Sin Ting, David Yap Fook Weng and Nurulfajar Bin Abdul Manap    

Abstract: PCA-based image compression is inherently limited by its matrix form and thus being restricted to work on block information only. In this study a novel approach is proposed to apply PCA technique on arbitrary shape ROI instead of rectangular or square ROI only. Based on factorization, this method successfully compresses arbitrary-shape ROI of an MRI brain image with different compression ratios using PCA. Simulation results show that no visible distortion were apparent on test image for total compression ratio as high as 80%.

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